Cross-cultural differences in visual attention: a computational modelling study

Literature in visual perception has identified that there are cross-cultural differences in visual perception [1]. Research comparing members of interdepended and collectivist East Asian cultures with independent and individualist European American cultures into picture perception showed that East Asians are more likely to attend the perceptual field as a whole and to focus on context and Westerns to focus on the salient foreground objects [1]. Research on cross-cultural differences has focused on investigating cross-cultural differences related to bottom-up information. Furthermore, research that experimentally manipulated the cultural norms of individualism and collectivism groups managed to attenuate cultural-specific preferences for social factors beneficial in human motivation [2]. Investigating the underlying mechanisms involved in these differences is very important as it can affect everyday tasks, advertisement and many other aspects of our everyday life. Here we present the first steps of this work, investigating the underlying processes in cross-cultural differences using computational modelling studies. The computational model is based on the spiking Search over Space and Time (sSoTS) model [3], that has been used to simulate Visual Attention task. sSoTS has incorporated mechanisms that allows us to investigate both bottomup and top-down processes. We show that sSoTS can successfully simulate cross-cultural differences in Visual attention involving bottom-up tasks. Moreover, we expand the studies by making predictions from the computational modelling studies for cross-cultural differences and top-down tasks

Model based analysis of fMRI-data: Applying the sSoTS framework to the neural basic of preview search.

The current work aims to unveil the neural circuits under- lying visual search over time and space by using a model-based analysis of behavioural and fMRI data. It has been suggested by Watson and Humphreys [31] that the prioritization of new stimuli presented in our visual field can be helped by the active ignoring of old items, a process they termed visual marking. Studies using fMRI link the marking pro- cess with activation in superior parietal areas and the precuneus [4, 18, 27, 26]. Marking has been simulated previously using a neural-level ac- count of search, the spiking Search over Time and Space (sSoTS) model, which incorporates inhibitory as well as excitatory mechanisms to guide visual selection. Here we used sSoTS to help decompose the fMRI signals found in a preview search procedure, when participants search for a new target whilst ignoring old distractors. The time course of activity linked to inhibitory and excitatory processes in the model was used as a regres- sor for the fMRI data. The results showed that different neural networks were correlated with top-down excitation and top-down inhibition in the model, enabling us to fractionate brain regions previously linked to vi- sual marking. We discuss the contribution of model-based analysis for decomposing fMRI data

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Simulating posterior parietal damage in a biologically plausible framework: neuropsychological tests of the search over time and space model.

The search over time and space (sSoTS) model attempts to simulate both the spatial and the temporal aspects of human visual search using spiking level neurons, which incorporate some biologically plausible aspects of neuronal firing. The model contains pools of units that (a) code basic features of objects, presumed to reside in the ventral visual stream, and (b) respond in a feature-independent way to stimulation at their location, presumed to operate in the posterior parietal cortex. We examined the effects of selective lesioning neurons responding to one side of the location map. Unilateral damage introduced spatial biases into selection that affected conjunction more than single-feature search. In addition, there was an impaired ability to segment stimuli over time as well as space (e.g., in preview search). These results match previously reported data on patients with posterior parietal lesions. In addition we show that spatial biases in selection increase under conditions in which there is decreased activity from excitatory neurotransmitters, mimicking effects of reduced arousal. Further simulations explored the effects of time and of visual grouping on extinction, generating predictions that were then tested empirically. The model provides a framework for linking behavioural data from patients with neural-level determinants of visual attention

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time and space model (sSoTS).

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space

Cultural differences in visual perceptual learning

Cultural differences in visual perceptual learning (VPL) could be attributed to differences in the way that people from individualistic and collectivistic cultures preferentially attend to local objects (analytic) or global contexts (holistic). Indeed, individuals from different cultural backgrounds can adopt distinct processing styles and learn to differentially construct meaning from the environment. Therefore, the present work investigates if cross-cultural differences in VPL can vary as a function of holistic processing. A shape discrimination task was used to investigate whether the individualistic versus collectivistic backgrounds of individuals affected the detection of global shapes embedded in cluttered backgrounds. Seventy-seven participants—including Asian (collectivistic background) and European (individualistic background) students—were trained to discriminate between radial and concentric patterns. Singelis's self-construal scale was also used to assess whether differences in learning could be attributed to independent or interdependent self-construal. Results showed that collectivists had faster learning rates and better accuracy performance than individualists following training—thereby reflecting their tendency to attend holistically when learning to extract global forms. Further, we observed a negative association between independent self-construal—which has previously been linked to analytic processing—with performance. This study provides insight into how socio-cultural backgrounds affect VPL

Attentional deficits in Alzheimer’s: investigating the role of acetylcholine with computational modelling

Attention is a very important cognitive process that is employed for many actions in our everydaylife (e.g. watching television, reading a paper, washing our face, eatingand so on). It is therefore essential to investigate further the underlying mechanisms inneuro-degenerativeconditions, like Alzheimer’s disease, in which ourattentional abilities are reduced(Festa, Heindel, & Ott, 2010; Foster, Behrmann, & Stuss, 1999; Hao et al., 2005; Porter, Tales, et al., 2010; Redel et al., 2012; A. Tales et al., 2002a; Vallejo et al., 2016).Alzheimer’s disease is a condition that can take severalyears if not decades from the time it starts to the time the full symptoms are shown (Tijms & Visser, 2018).In those years of disease progression,there are a number of pathological processes that are taking place, however one of the starting point of the pathologyis believed to be the aggregation of βamyloids into plaques(Gordon et al., 2018; Tijms & Visser, 2018). Irrespective ofthe amount of research that has taken place,manyquestionsremain on how the disease unfolds and how to identify individual’s position in the disease’s trajectory(Gordon et al., 2018; Ryman et al., 2014)